99 citations · 119 across the 6 of their papers we have counts for
6 papers
NodeSyn: Socially Aligned Synthetic Data for AI Evaluation
Qazi Mamunur Rashid, Xuan Yang, Zhengzhe Yang +5
Recent advancements in generative AI facilitate large-scale synthetic data generation for model evaluation. However, without targeted approaches, these datasets often lack the soci…
Cultural Perspectives and Expectations for Generative AI: A Global Survey Approach
Erin van Liemt, Renee Shelby, Andrew Smart +5
There is a lack of empirical evidence about global attitudes around whether and how GenAI should represent cultures. This paper assesses understandings and beliefs about culture as…
Amplify Initiative: Building A Localized Data Platform for Globalized AI
Qazi Mamunur Rashid, Erin van Liemt, Tiffany Shih +19
Current AI models often fail to account for local context and language, given the predominance of English and Western internet content in their training data. This hinders the glob…
A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models
Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres +27
Large language models (LLMs) hold promise to serve complex health information needs but also have the potential to introduce harm and exacerbate health disparities. Reliably evalua…
The Equitable AI Research Roundtable (EARR): Towards Community-Based Decision Making in Responsible AI Development
Jamila Smith-Loud, Andrew Smart, Darlene Neal +14
This paper reports on our initial evaluation of The Equitable AI Research Roundtable -- a coalition of experts in law, education, community engagement, social justice, and technolo…
Dialog Inpainting: Turning Documents into Dialogs
Zhuyun Dai, Arun Tejasvi Chaganty, Vincent Zhao +4
Many important questions (e.g. "How to eat healthier?") require conversation to establish context and explore in depth. However, conversational question answering (ConvQA) systems…